Technology advancements and cost reductions over time have enabled computers to become commonplace in society. Enterprises employ computers to collect and analyze data. For instance, computers can be employed to capture data about business customers that can be utilized to track sales and/or customer demographics. In addition, individuals interact with a plurality of non-enterprise computing devices including home computers, laptops and mobile devices (e.g., smartphones and personal digital assistants (PDAs)). As a consequence of computer ubiquity, an enormous quantity of digital data is generated daily by both enterprises and individuals.
Large quantities of such data are housed in one or more databases and/or data warehouses. A database is a collection of data or facts organized in a systematic manner and persisted to a storage device. For example, relational data storage systems (e.g., DB2, SQL Server, MySQL . . . ) are frequently utilized to store relational data and manage these of relationships. A data warehouse is a much larger repository composed of a plurality of databases. In one instance, businesses can store customer information (e.g., name, address, product(s) purchased, date, location . . . ) to one or more data databases. For example, a transactional database can capture current data and aged data can be pushed to a warehouse. In another instance, entity and/or individual web pages can be housed in one or more databases.
The collection and management of such vast amounts of enterprise data provides tremendous opportunities and advantages. Enterprise data can be used to track and control inventory, to predict sales and to determine pricing. Such information can have tremendous value to an organization. For example, a retailer's customer lists are considered a vital business asset.
However, the value of data is directly related to its accessibility. If the data cannot be efficiently retrieved from storage in a manner that allows it to be easily analyzed and processed, the utility of the data is greatly reduced. In addition, long delays or latencies in loading or processing data reduce efficiency and frequently lead to user frustration.